Accurately Automating Dataset Labelling Using Amazon SageMaker GroundTruth (Level 200)
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03.04.19 – 4 69026:33Популярные
Опубликовано 3 апреля 2019, 17:44
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Successful machine learning models are built on high-quality training datasets. Labeling raw data to get accurate training dataset involves a lot of time and effort, because sophisticated models can require thousands of labeled examples to learn from, before they produce good results. Typically, the task of labeling is distributed across large number of humans, adding significant overheads and costs. In this session, learn how Amazon SageMaker Ground Truth can solve data labeling problems, build highly-accurate training datasets, and achieve automated labeling.
Speaker: Will Badr, Senior Technical Account Manager, AWS Enterprise Support, ANZ
Successful machine learning models are built on high-quality training datasets. Labeling raw data to get accurate training dataset involves a lot of time and effort, because sophisticated models can require thousands of labeled examples to learn from, before they produce good results. Typically, the task of labeling is distributed across large number of humans, adding significant overheads and costs. In this session, learn how Amazon SageMaker Ground Truth can solve data labeling problems, build highly-accurate training datasets, and achieve automated labeling.
Speaker: Will Badr, Senior Technical Account Manager, AWS Enterprise Support, ANZ
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